955 resultados para multispectral image analysis
Resumo:
The dataset is composed of 41 samples from 10 stations. The phytoplankton samples were collected by 5l Niskin bottles attached to the CTD system. The sampling depths were selected according to the CTD profile and the in situ fluorometer readings: surface, temperature, salinity and fluorescence gradients and 1 m above the bottom. At some stations phytoplankton net samples (20 µm mesh-size) were collected to assist species biodiversity examination. The samples (1l sea water) were preserved in 4% buffered to pH 8-8.2 with disodiumtetraborate formaldehyde solution and stored in plastic containers. On board at each station few live samples were qualitatively examined under microscope for preliminary analysis of taxonomic composition and dominant species. The taxon-specific phytoplankton abundance samples were concentrated down to 50 cm**3 by slow decantation after storage for 20 days in a cool and dark place. The species identification was done under light microscope OLIMPUS-BS41 connected to a video-interactive image analysis system at magnification of the ocular 10X and objective - 40X. A Sedgwick-Rafter camera (1ml) was used for counting. 400 specimen were counted for each sample, while rare and large species were checked in the whole sample (Manual of phytoplankton, 2005). Species identification was mainly after Carmelo T. (1997) and Fukuyo, Y. (2000). Total phytoplankton abundance was calculated as sum of taxon-specific abundances. Total phytoplankton biomass was calculated as sum of taxon-specific biomasses. The cell biovolume was determined based on morpho-metric measurement of phytoplankton units and the corresponding geometric shapes as described in detail in (Edier, 1979).
Resumo:
The samples were concentrated down to 50 cm**3 by slow decantation after storage for 20 days in a cool and dark place. The species identification was done under light microscope OLIMPUS-BS41 connected to a video-interactive image analysis system at magnification of the ocular 10X and objective - 40X. A Sedgwick-Rafter camera (1ml) was used for counting. 400 specimen were counted for each sample, while rare and large species were checked in the whole sample (Manual of phytoplankton, 2005). Species identification was mainly after Carmelo T. (1997) and Fukuyo, Y. (2000). Taxon-specific phytoplankton abundance and biomass were analysed by Moncheva S., B. Parr, 2005. Manual for Phytoplankton Sampling and Analysis in the Black Sea. The cell biovolume was determined based on morpho-metric measurement of phytoplankton units and the corresponding geometric shapes as described in detail in (Edier, 1979).
Resumo:
Traditional identification of ore minerals with reflected light microscopy relies heavily on the experience of the observer. Qualified observers have become a rarity, as ore microscopy is often neglected in today’s university training, but since it furnishes necessary and inexpensive information, innovative alternatives are needed, especially for quantification. Many of the diagnostic optical properties of ores defy quantification, but recent developments in electronics and optics allow new insights into the reflectance and colour properties of ores. Preliminary results for the development of an expert system aimed at the automatic identification of ores based on their reflectance properties are presented. The discriminatory capacity of the system is enhanced by near IR reflectance measures, while UV filters tested to date are unreliable. Interaction with image analysis software through a wholly automated microscope, to furnish quantitative and morphological information for geometallurgy, relies on automated identification of the ores based on the measured spectra. This methodology increases enormously the performance of the microscopist; nevertheless supervision by an expert is always needed.
Resumo:
This paper proposes a new methodology for object based 2-D data fu- sion, with a multiscale character. This methodology is intended to be use in agriculture, specifically in the characterization of the water status of different crops, so as to have an appropriate water management at a farm-holding scale. As a first approach to its evaluation, vegetation cover vigor data has been integrated with texture data. For this purpose, NDVI maps have been calculated using a multispectral image and Lacunarity maps from the panchromatic image. Preliminary results show this methodology is viable in the integration and management of large volumes of data, which characterize the behavior of agricultural covers at farm-holding scale.
Resumo:
We propose a level set based variational approach that incorporates shape priors into edge-based and region-based models. The evolution of the active contour depends on local and global information. It has been implemented using an efficient narrow band technique. For each boundary pixel we calculate its dynamic according to its gray level, the neighborhood and geometric properties established by training shapes. We also propose a criterion for shape aligning based on affine transformation using an image normalization procedure. Finally, we illustrate the benefits of the our approach on the liver segmentation from CT images.
Resumo:
El objetivo principal del proyecto es la realización de una aplicación en el programa MATLAB. En primer lugar, realizaremos un estudio teórico relativo al tema de nuestro proyecto. En nuestro caso como el tema es Imagen y Televisión, explicaremos de forma teórica la información principal acerca del Tratamiento Digital de la Imagen. Una vez conocida las técnicas principales utilizadas en el tratamiento digital, realizaremos un estudio exhaustivo en las técnicas actuales que existen acerca del análisis de imágenes. Daremos una breve explicación mostrando en qué consiste esta técnica, los diferentes pasos que se llevan a cabo en una imagen para su análisis, explicando brevemente cada unos de ellos y enumerando algunas técnicas para la realización de cada una de ellas. Tras esta primera parte, nos centraremos en las técnicas de correlación de imágenes (DIC). Explicaremos como han surgido estas técnicas, cual son sus principales conceptos, sus inicios y las ventajas e inconvenientes que tienen. Dentro de las diferentes técnicas de correlación de imágenes, explicaremos de forma detallada la correspondencia por áreas, ya que es la técnica que vamos a utilizar para la realización del proyecto. Explicaremos en qué consiste, y desarrollaremos teóricamente cual son los pasos que se deben realizar en las imágenes para realizar esta técnica. Explicaremos cual es su terminología, y cuáles son los posibles defectos que puede tener esta técnica. Finalmente, una vez estudiada la teoría, realizaremos una sencilla aplicación que nos permita evaluar y encontrar las diferencias en una secuencia de imágenes. El programa utilizado para este proyecto es MATLAB, que es un programa matemático, utilizado enormemente en el ámbito de la ingeniería. Mediante esta aplicación obtendremos dos figuras, una de ellas donde veremos los vectores de movimiento que existen entre las dos imágenes y la segunda, donde obtendremos el factor de correlación que hay entre las dos imágenes. ABSTRACT OF MY PROJECT The main objective of the project is the development of an application in MATLAB program. Firstly carry out a theoretical study on the topic of our project. In our case as the theme is Picture and Television, we explain the main information about Digital Image Processing. Once known the main techniques used in digital images, we will make a study on current techniques that exist about image analysis. We will give a brief explanation showing what this technique is, the different steps that are performed on an image for analysis, briefly explaining each of them and listing some techniques for performing each. After this first part, we will focus on the techniques of image correlation (DIC). We explain how these techniques have emerged, which are the main concepts, the beginning and the advantages and disadvantages they have. There are different image correlation techniques. We will explain in detail the correspondence areas, as it is the technique that we will use for the project. Explain what it is, which is theoretically and we develop steps that must be performed on the images for this technique. We explain what their terminology is, and what are the possible defects that may have this technique. Finally, having explored the theory images, we will make a simple application that allows us to evaluate and find differences in a sequence of images. The program used for this project is MATLAB, a mathematical program, widely used in the field of engineering. Using this application will get two figures, one where we will see the motion vectors between the two images and the second where we get the correlation factor between the two images.
Resumo:
Image analysis could be a useful tool for investigating the spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to define apparent soil moisture patterns from vertical planes of Vertisol pit images and (ii) to describe the scaling of apparent soil moisture distribution using fractal parameters.
Resumo:
Image analysis could be a useful tool for investigating the spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to define apparent soil moisture patterns from vertical planes of Vertisol pit images and (ii) to describe the scaling of apparent soil moisture distribution using fractal parameters. Twelve soil pits (0.70 m long × 0.60 m width × 0.30 m depth) were excavated on a bare Mazic Pellic Vertisol. Six of them were excavated in April/2011 and six pits were established in May/2011 after 3 days of a moderate rainfall event. Digital photographs were taken from each Vertisol pit using a Kodak™ digital camera. The mean image size was 1600 × 945 pixels with one physical pixel ≈373 μm of the photographed soil pit. Each soil image was analyzed using two fractal scaling exponents, box counting (capacity) dimension (DBC) and interface fractal dimension (Di), and three prefractal scaling coefficients, the total number of boxes intercepting the foreground pattern at a unit scale (A), fractal lacunarity at the unit scale (Λ1) and Shannon entropy at the unit scale (S1). All the scaling parameters identified significant differences between both sets of spatial patterns. Fractal lacunarity was the best discriminator between apparent soil moisture patterns. Soil image interpretation with fractal exponents and prefractal coefficients can be incorporated within a site-specific agriculture toolbox. While fractal exponents convey information on space filling characteristics of the pattern, prefractal coefficients represent the investigated soil property as seen through a higher resolution microscope. In spite of some computational and practical limitations, image analysis of apparent soil moisture patterns could be used in connection with traditional soil moisture sampling, which always renders punctual estimates
Resumo:
Con este trabajo se pretende determinar la relación entre las características físicas y mecánicas y la estructura para espumas de aluminio de Al12Si y AA6061 obtenidas por pulvimetalurgia utilizando probetas prismáticas de dimensiones diecisiete por diecisiete por sesenta milímetros. De su estudio mecánico y de análisis de imagen se concluye que las probetas cuyas propiedades físicas y mecánicas están moderadamente por encima de la media poseen mayor número de poros medianos y paredes de poro más gruesas. Por el contrario, las propiedades resultan inferiores cuando se presentan estructuras con un mayor número de poros medianos. Aquellas espumas con estructuras obtenidas por una espumación incompleta presentan una menor porosidad y por ello mayores densidades. En aquellos casos donde la estructura presenta una elevada presencia de poros grandes, sus propiedades mecánicas disminuyen. ABSTRACT With this work we are trying to determine the relation between physical and mechanical characteristics and its structure, for Al12Si and AA6061 aluminium foams, obtained by podwer metallurgy. Aluminium foam samples with dimensions of seventeen per seventeen per sixty millimeters were used. After its mechanical and image analysis study, we conclude that samples whose physical and mechanical properties are moderately over the average, they have a major proportion of medium pores and thicker pore walls. Otherwise, properties result to be inferior when a major number of medium pores structures are presented. Those foam structures obtained with an incomplete foaming process show a lower porosity, and so higher densities. Also, properties decrease in those cases in which the structure presents a high presence of big pores.
Resumo:
Image analysis could be a useful tool for investigating the spatial patterns of apparent soil moisture at multiple resolutions. The objectives of the present work were (i) to define apparent soil moisture patterns from vertical planes of Vertisol pit images and (ii) to describe the scaling of apparent soil moisture distribution using fractal parameters. Twelve soil pits (0.70 m long × 0.60 m width × 0.30 m depth) were excavated on a bare Mazic Pellic Vertisol. Six of them were excavated in April/2011 and six pits were established in May/2011 after 3 days of a moderate rainfall event. Digital photographs were taken from each Vertisol pit using a Kodak? digital camera. The mean image size was 1600 × 945 pixels with one physical pixel ?373 ?m of the photographed soil pit. Each soil image was analyzed using two fractal scaling exponents, box counting (capacity) dimension (DBC) and interface fractal dimension (Di), and three prefractal scaling coefficients, the total number of boxes intercepting the foreground pattern at a unit scale (A), fractal lacunarity at the unit scale (?1) and Shannon entropy at the unit scale (S1). All the scaling parameters identified significant differences between both sets of spatial patterns. Fractal lacunarity was the best discriminator between apparent soil moisture patterns. Soil image interpretation with fractal exponents and prefractal coefficients can be incorporated within a site-specific agriculture toolbox. While fractal exponents convey information on space filling characteristics of the pattern, prefractal coefficients represent the investigated soil property as seen through a higher resolution microscope. In spite of some computational and practical limitations, image analysis of apparent soil moisture patterns could be used in connection with traditional soil moisture sampling, which always renders punctual estimates.
Resumo:
The energy and specific energy absorbed in the main cell compartments (nucleus and cytoplasm) in typical radiobiology experiments are usually estimated by calculations as they are not accessible for a direct measurement. In most of the work, the cell geometry is modelled using the combination of simple mathematical volumes. We propose a method based on high resolution confocal imaging and ion beam analysis (IBA) in order to import realistic cell nuclei geometries in Monte-Carlo simulations and thus take into account the variety of different geometries encountered in a typical cell population. Seventy-six cell nuclei have been imaged using confocal microscopy and their chemical composition has been measured using IBA. A cellular phantom was created from these data using the ImageJ image analysis software and imported in the Geant4 Monte-Carlo simulation toolkit. Total energy and specific energy distributions in the 76 cell nuclei have been calculated for two types of irradiation protocols: a 3 MeV alpha particle microbeam used for targeted irradiation and a 239Pu alpha source used for large angle random irradiation. Qualitative images of the energy deposited along the particle tracks have been produced and show good agreement with images of DNA double strand break signalling proteins obtained experimentally. The methodology presented in this paper provides microdosimetric quantities calculated from realistic cellular volumes. It is based on open-source oriented software that is publicly available.